Propagation of precipitation measurement biases into the hydraulic modelling of urban drainage systems: a case study

Abstract

Precipitation is the primary source of freshwater, while it can have great socio-economical impacts associated with extreme weather events such as floods and droughts. Good quality hydro-meteorological data is an essential condition not only for climate analysis but also for warning systems, hydraulic structures design, risk assessment, etc. In fact, precipitation is one of the most intensively used variables in hydrological modelling and its measurement accuracy is of foremost importance (Peterson et al., 1998). Accurate and timely knowledge of precipitation characteristics at urban and natural basins scales is essential for understanding how different catchment hydrological systems operate under changing climatic conditions and for improved applications that range from flash flood prediction to freshwater resource management. Difficulties in achieving accurate measurements arise from various instrumental and environmental sources of systematic biases, resulting in a significant underestimation or overestimation of precipitation in terms of rainfall depth or intensity. Instrumental errors are systematic and related to the sensor specifications (sensitivity, measuring principle), allowing correction techniques based on laboratory test (Lanza & Stagi, 2009; Colli et al., 2013; Colli et al., 2014). Although several attempts made to standardize measurements procedure, this has never been successfully achieved. Traditional rain gauges provide, still nowadays, the only direct measurement of precipitation. These allow a high measurement resolution in time but are local in nature, and the obtained information is often referred to as “point precipitation”. In order to provide sufficient coverage of the catchment area of hydrological basins, multiple instruments are needed, while interpolation methods are used to fill in the area between the gauge locations. Aim of this study is to evaluate the impact of Precipitation Measurement Biases (PMBs) of tipping bucket rain gauges into the hydraulic modelling of urban drainage networks. As a case study, the monitored experimental suburban catchment of Parco d’Orleans located in the University Campus of Palermo, Italy